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Method for accurately identifying parameters of thermal process state-space model by adopting improved genetic optimization algorithm

A process state and space model technology, applied in the engineering field, to achieve enhanced capabilities, enhanced local optimization capabilities, and the effect of avoiding random search phenomena in the later stage

Active Publication Date: 2017-05-10
SOUTHEAST UNIV
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Problems solved by technology

[0005] Therefore, the basic genetic algorithm (SGA) often produces premature phenomena when solving high-dimensional, nonlinear complex system problems.

Method used

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  • Method for accurately identifying parameters of thermal process state-space model by adopting improved genetic optimization algorithm
  • Method for accurately identifying parameters of thermal process state-space model by adopting improved genetic optimization algorithm
  • Method for accurately identifying parameters of thermal process state-space model by adopting improved genetic optimization algorithm

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Embodiment Construction

[0045] Main steps of the present invention are as follows:

[0046] Define the fitness value as:

[0047]

[0048] In the above formula, q, the number of output variables, α j The weight corresponding to the jth output variable, y(k) is the actual output of the system, is the model calculation output, and N is the total number of measured data. The improved genetic algorithm is optimized, that is, to find a set of identification parameters, so that the fitness value J is the minimum.

[0049] The process design of the thermal process state space model identification scheme is as follows:

[0050] 1. Determine the structure and identification parameters of the model

[0051] The state-space model can generally be written as

[0052]

[0053] in, Be the derivative of the n-dimensional state variable, X is the n-dimensional state variable, n is the number of state variables, A=A(X), A(X) is a function about the state variable X, n×n matrix A is a system matrix, B=B...

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Abstract

The invention discloses a method for accurately identifying parameters of a thermal process state-space model by adopting an improved genetic optimization algorithm. The method mainly comprises the steps of determining structure and identification parameters of the model, determining structural parameters of the optimization algorithm, solving a fitness value, encoding, transforming a decimal system into a binary system, performing optimal chromosome high-frequency mutation, implementing an optimal chromosome preservation mechanism, a selection operator, a crossover and mutation operators, decoding, transforming the binary system into a decimal system, and performing adaptive spatial mutation. According to the invention, the optimal chromosome preservation mechanism is introduced, so that random search of the algorithm in a later period can be avoided; the global optimization ability of the algorithm can be enhanced through optimal chromosome high-frequency mutation; and a certain range of real number spatial mutation is performed on a global optimal solution through adaptive spatial mutation, the range of spatial mutation increase along with increase in algebras trapping in local optimum until a local optimal solution jumps out, and the local optimization ability of the algorithm can be enhanced.

Description

technical field [0001] The invention belongs to the technical field of engineering, in particular to a method for accurately identifying parameters of a thermal process state space model by using an improved genetic optimization algorithm. Background technique [0002] Realistic thermal process models are mostly nonlinear, large delay, large inertia, and nonlinear state-space models. At present, the basic genetic algorithm is generally used to realize. [0003] The basic genetic algorithm (SGA) is an evolutionary search algorithm based on the natural selection mechanism of the survival of the fittest and biological genetics. Its main feature is the group search strategy, which has strong global search ability and has no prior knowledge of the optimized mathematical model. It is widely used in the fields of automatic control, image recognition, machine learning and fault diagnosis, but it also exposes many shortcomings and defects in its theory and technology. [0004] Ther...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 范赫张雨飞
Owner SOUTHEAST UNIV
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